Beamforming transmission is one of the wireless communication techniques, and has been researched and developed in a variety of fields such as radar techniques, sonar techniques, earthquake seismology, and medical devices such as an ultrasonograph. In these years, this beamforming transmission has been also introduced into standards such as IEEE (Institute of Electrical and Electronics Engineers) 802.16e and LTE (Long Term Evolution) of 3GPP (3rd Generation Partnership Project).
The beamforming transmission can provide many practical functions not implemented in other solutions. For example, the beamforming transmission can enhance cell throughput gain by multi-user transmission of individual beams defining multi-beams toward different user equipments (UEs), and extend a receiving area (coverage) by beamforming gain.
The beamforming transmission can be classified into two types. One is fixed-beamforming transmission, which utilizes spatial processing by an antenna array to fix a pattern of a beam to be transmitted. The other is adaptive beamforming transmission, which also utilizes a spatial processing manner to adaptively define a beam to be transmitted based on both a desired wave and an interference wave.
Fixed multi-beam transmission is used in order to, for example, increase the number of simultaneously active users (UEs), and can provide high (communication) capacity in totality depending on the number of the beams or the antenna arrays. In order to achieve high performance in the fixed multi-beam transmission, optimum beams must be selected for transmission and reception of the independent UEs. This can improve SINR (Signal-to-Interference and Noise power Ratio). The fixed multi-beam can be generated by, for example, a Rotman lens.
In contrast, the adaptive beamforming transmission is designed so as to increase its substantive (communication) capacity. This technique utilizes spatial processing by the antenna array, and requires optimum combination in order to improve its overall system performance. Optimum synthesis of beamforming with an adaptive array antenna optimises response of a beamformer so as to minimize the influence of noise from directions other than that of a desired signal and of interference on the output of the response.
A weight (coefficient) for the adaptive (optimum) beamforming is selected on the basis of, for example, use of MSC (Multiple Side-lobe Canceller) and RS (Reference Signal), Max-SNR (Signal to Noise Ratio), LCMV (linearly constrained minimum variance beamforming), and MVDR (Minimum Variance Distortion-less Response).
Such conventional technology about the adaptive beamforming is disclosed in, for example, the following documents.    [Patent Document 1] Japanese Laid-open Patent Publication No. 2007-6365    [Patent Document 2] Published Japanese Translation of a PCT Application, No. 2005-520386    [Nonpatent Document 1] S.-S. Jeng, G. Okamoto, G. Xu, H.-P. Lin, and W. Vogel, “Experimental evaluation of smart antenna system performance for wireless communications”, IEEE Trans. Antenna Propag., vol. 46, pp. 749-757, 1998.    [Nonpatent Document 2] IEEE 802.16e, Draft IEEE Standard for Local and Metropolitan Area networks, Oct. 14, 2005.    [Nonpatent Document 3] Y. M. Tao, G. Y. Delisle, “Lens-fed multiple beam array for millimeter wave indoor communications”, Volume 4, pp. 2206-2209, Jul. 13-18, 1997.    [Nonpatent Document 4] D. H. Johnson and D. E. Dudgeon, Array Signal Processing: Concepts and Techniques, Prentice-Hall, Inc., 1993.    [Nonpatent Document 5] R. T. Compton, Jr., Adaptive Antennas: Concepts and Performance, Prentice-Hall, Englewood Clitts, N.J., 1988.    [Nonpatent Document 6] B. D. V. Veen and K. M. Buckley, “Beamforming: a versatile approach to spatial filtering”, IEEE ASSP Magazine, pp. 4-23, April 1988.    [Nonpatent Document 7] D. A. Pados and G. N. Karystinos, “An iterative algorithm for the computation of the MVDR filter”, IEEE Trans. On Signal Processing. Vol. 49, No 2, February 2001.    [Nonpatent Document 8] R. O. Schmidt, “Multiple emitter location and signal parameter estimation”, IEEE Trans. Antennas Propag., vol. 34, pp. 276-280, March 1986.    [Nonpatent Document 9] R. Roy and T. Kailath, “ESPRIT: Estimation of signal parameters via rotational invariance techniques”, IEEE Trans. Acoust., Speech, Signal Process., vol. 37, pp. 984-995, July 1989.
However, in the conventional technology, a transmitter such as a base station (BS) merely directs a beam to be directly transmitted toward a UE selected (scheduled) as a communication partner. Therefore, depending on directing the transmitted beam, interference with the receiving UE may significantly change. Such a change may affect the received quality of a wireless communication device such as SINR.